How do advanced epidemiological methods impact infection control?

Epidemiology is the science that studies the determinants and the distribution of diseases and risk factors in a population. Advanced epidemiological methods impact in infection control by making more accurate predictions about diagnosis and preventive measures.

What epidemiological methods are necessary for infection prevention and control?

The basic elements for epidemiological inferences are incidence rates. These measures require counting disease occurrence in relation to the people and time spans in which they occur. The basic epidemiological design is a cohort study in which incidence rates are compared in two populations of exposed and unexposed subjects.

A fine example of an incidence study in nosocomial infections was carried out by Haley et al, in which data collected on 136,516 patients from 276 hospitals studied in the SENIC Project (Study on the Efficacy of Nosocomial Infection Control) were used to compare validly the nosocomial infection rates in groups of patients studied from different time periods and/or different hospitals.

Incidence rates are not easy to obtain and, very often, it is necessary to go in search for cooperation from numerous other people to collect the data. In some circumstances, the logistic problems encountered in measuring disease incidence have led many to choose a case-control study as a basic epidemiological type of study. Cohort studies and case control are the most common epidemiological study designs used in infection control to assess causation.

Recently incorporated epidemiological study designs are systematic reviews and meta-analysis. Systematic review is a literature review focused in a single question that tries to identify, appraise, select and synthesize all high quality research evidence relevant to that question. When the literature review uses statistical techniques to combine these valid studies it is called meta-analysis.

What are the conclusions of clinical trials or meta-analyses regarding advanced epidemiological methods that guide infection control policy?

Healthcare-associated infections and their impact on healthcare systems have been addressed historically by infection control policies based on barrier precautions and patient isolation. However, as important as infection control policies are, health care workers adherence to these policies varies. Therefore, research evaluating changes in healthcare workers' behavior for reducing healthcare associated infections are mandatory. Considering the multi-factorial components of the problem and the logistical and unethical difficulties of carrying out randomized controlled trials, it may be necessary to incorporate an appraisal of bundled behavioral interventions by means of meta-analysis of observational studies.

What are the consequences of ignoring advanced epidemiological methods?

Ignoring key concepts related to advanced epidemiological methods can lead to mistakes in understanding the causes of diseases. Historically physicians have collaborated with statisticians who contributed expertise in data analyses. A negative influence from statisticians has been the interpretation of data based on statistical hypothesis testing. This misapplication of statistics occurs very often in the area of multivariate modeling where the use of correlation coefficients, stepwise algorithms, and variance reduction to evaluate the model substitute the underlying epidemiological concept that should guide the analysis.

What other information supports advanced epidemiological methods?

Hypothesis generation and testing using advanced epidemiological methods provide causative explanations for outbreaks. Confirmation about the validity of such hypothesis occurs at the end of the outbreak after intervention on the epidemic pathway. In the literature, there are many examples about how case-control studies have served to identify the association between the exposure and the disease condition.

A case control study served to incriminate the theft of fentanyl and substitution of predrawn syringes by distilled water contaminated by P. pickettii in a hospital that analyzed a small outbreak of 3 patients with nosocomially-acquired Pseudomonas pickettii bacteremia. The outbreak ended when the identified health care worker was asked to leave the institution.

Another example was the use of epidemiologic tools to identify a decorative water fountain as the source of an outbreak of Legionnaires disease in a stem cell transplantation unit. Two patients developed pneumonia after 10 days of completing radiation therapy, and each reported having observed the fountain at close range.

There are many examples in the literature supporting the usefulness of epidemiologic methods to identify the origin of outbreaks and how to intervene to stop them.

Summary of current controversies.

The abuse of statistical significance. Statistical hypothesis testing was motivated originally to provide a basis for decision making in agriculture and quality control experiments so the results could be classified into discrete categories. Studies should define the association between variables not only based on statistical hypothesis but also by confidence intervals.

The use of multivariate analysis with a statistical interpretation of data instead of using epidemiological concepts of disease causation.

Conclusions from systematic reviews and meta-analysis could be flawed by publication bias. Researchers should invest time and effort to identify published and unpublished information regarding the research topic.

What is the impact of advanced epidemiological methods relative to the impact of other infection control methods?

Epidemiological methods have served to grade the quality of evidence from epidemiological studies and categorize the strength of recommendations for infection control in clinical guidelines. The following is the system of grading used by the Infectious Diseases Society of America–United States Public Health Service.

Strength of recommendation:

Good evidence to support a recommendation for use.

Moderate evidence to support a recommendation for use.

Poor evidence to support a recommendation.

Moderate evidence to support a recommendation against use.

Good evidence to support a recommendation against use.

Quality of evidence:

Evidence from equal or more than 1 properly randomized, controlled trial.

Evidence from equal or more than 1 well-designed clinical trial, without randomization; from cohort or case-controlled analytic studies (preferably from more than 1 center); from multiple time-series; or from dramatic results from uncontrolled experiments.

Evidence from opinions of respected authorities, based on clinical experience, descriptive studies, or reports of expert committees.

Overview of important clinical trials, meta-analyses, case control studies, case series, and individual case reports related to infection control and advanced epidemiological methods.

Advanced epidemiological methods have been used in the research of health-care associated infections to assess the individual contribution of a risk factor, to assess the etiological fraction, to determine the etiology of an outbreak and to assess the effectiveness of preventive and therapeutical interventions in infection control.

Controversies in detail.

Controversies regarding advance epidemiological methods can be summarized the following aspects:

Lack of knowledge of all causal components. Sometimes it is not possible to measure the individual risks, and assigning the average value to everyone in the category reflects our inability to determine all possible determinants related to acquiring an infection for that particular patient in that category.

Using sole statistical modeling as hypothesis testing to define the complete causal mechanism that explains a disease or outbreak.

Lack of quality in reporting research projects leading to inability to address the presence and degree of bias by reviewers of the study.

What national and international guidelines exist?

During the last two decades, several groups of researchers have developed guidelines and consensus statements addressing the quality of conduction and of reporting epidemiological studies. Table I describes the list of various types of research methods, the identified guidelines, statements and proposals as well as the internet address for their retrieval.

Table I.

Guidelines and consensus statements on quality of conduction and reporting of epidemiological studies

What other consensus group statements exist, and what do key leaders advise?

Regarding consensus group statements, there are many society guidelines addressing antibiotic agents use, infections by organ system, and infections by organisms and other issues guidelines. However, recommendations in the current guidelines are supported in most cases by low quality evidence. According to a recent review study on the Infectious Disease Society of America (IDSA) guideline recommendations, most guidelines were based on low‐quality evidence derived from nonrandomized studies or expert opinion. These findings highlight the limitations of current clinical infectious diseases research that can provide high‐quality evidence. Therefore, the authors conclude that there is an urgent need to support high‐quality research to strengthen the evidence available for the formulation of guidelines.

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